655 resultados para recursive detrending


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A discussion of nonlinear dynamics, demonstrated by the familiar automobile, is followed by the development of a systematic method of analysis of a possibly nonlinear time series using difference equations in the general state-space format. This format allows recursive state-dependent parameter estimation after each observation thereby revealing the dynamics inherent in the system in combination with random external perturbations.^ The one-step ahead prediction errors at each time period, transformed to have constant variance, and the estimated parametric sequences provide the information to (1) formally test whether time series observations y(,t) are some linear function of random errors (ELEM)(,s), for some t and s, or whether the series would more appropriately be described by a nonlinear model such as bilinear, exponential, threshold, etc., (2) formally test whether a statistically significant change has occurred in structure/level either historically or as it occurs, (3) forecast nonlinear system with a new and innovative (but very old numerical) technique utilizing rational functions to extrapolate individual parameters as smooth functions of time which are then combined to obtain the forecast of y and (4) suggest a measure of resilience, i.e. how much perturbation a structure/level can tolerate, whether internal or external to the system, and remain statistically unchanged. Although similar to one-step control, this provides a less rigid way to think about changes affecting social systems.^ Applications consisting of the analysis of some familiar and some simulated series demonstrate the procedure. Empirical results suggest that this state-space or modified augmented Kalman filter may provide interesting ways to identify particular kinds of nonlinearities as they occur in structural change via the state trajectory.^ A computational flow-chart detailing computations and software input and output is provided in the body of the text. IBM Advanced BASIC program listings to accomplish most of the analysis are provided in the appendix. ^

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Background: Squamous cell carcinoma of the oropharynx (SCCOP) is characterized by local tumor aggressiveness, high recurrence rates, a high incidence of second primary tumors, and medical comorbidities. Significant trends in demographic and clinical characteristics as well as survival among SCCOP patients have been observed over time, likely owing to the changing etiology of the disease. Human papillomavirus type 16 (HPV16) infection is associated with a significant proportion of these cancers. Biomarkers that may aid in identifying patients that are at higher risk of recurrence and death are important so that these patients may be followed more closely to improve their quality of life. ^ Study population and methods: The retrospective review (Specific Aim 2) included 3891 newly diagnosed, previously untreated patients presenting to our institution between 1955 and 2004. A total of 2299 patients treated at our institution were included in survival and recursive partitioning analysis. The prospective cohort study (Specific Aim 3) included 266 patients presenting to our institution between January 2006 and September 2009. ^ Results: The results from the retrospective review showed that over time, patients presented at younger ages and were more likely to have base of tongue/tonsil tumors and to be never/former smokers and moreover survival improved significantly over time. In survival and recursive partitioning analyses, the TNM staging system was efficient in prognosticating patients prior to 1995. However, in the recent decade, the TNM staging system was completely inadequate. The factors having the greatest positive effect on overall survival since 1995 were those common to HPV-associated SCCOP. The results from the prospective cohort study indicate that patients with high nodal stage and those with late stage disease have increased levels of pretreatment serum HPV DNA. ^ Conclusions: We saw a distinct improvement in survival among SCCOP patients over the past 50 years at our institution. The main factors contributing to this were changes in clinical characteristics, in particular surrogates for HPV status. The current TNM staging system for SCCOP is inadequate and incorporation of HPV status (and perhaps smoking status) is encouraged. Furthermore, although pretreatment circulating levels of HPV DNA was associated with higher N category and overall disease stage, it has limited utility as a marker for recurrence among SCCOP patients.^

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Quasi-periodic variation in sea-surface temperature, precipitation, and sea-level pressure in the equatorial Pacific known as the El Niño - Southern Oscillation (ENSO) is an important mode of interannual variability in global climate. A collapse of the tropical Pacific onto a state resembling a so-called 'permanent El Niño', with a preferentially warmed eastern equatorial Pacific, flatter thermocline, and reduced interannual variability, in a warmer world is predicted by prevailing ENSO theory. If correct, future warming will be accompanied by a shift toward persistent conditions resembling El Niño years today, with major implications for global hydrological cycles and consequent impacts on socioeconomic and ecological systems. However, much uncertainty remains about how interannual variability will be affected. Here, we present multi-annual records of climate derived from growth increment widths in fossil bivalves and co-occurring driftwood from the Antarctic peninsula that demonstrate significant variability in the quasi-biennial and 3-6 year bands consistent with ENSO, despite early Eocene (~50 Mya) greenhouse conditions with global average temperature -10 degrees higher than today. A coupled climate model suggests an ENSO signal and teleconnections to this region during the Eocene, much like today. The presence of ENSO variation during this markedly warmer interval argues for the persistence of robust interannual variability in our future greenhouse world.

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The identification in various proxy records of periods of rapid (decadal scale) climate change over recent millennia, together with the possibility that feedback mechanisms may amplify climate system responses to increasing atmospheric CO2, highlights the importance of a detailed understanding, at high spatial and temporal resolutions, of forcings and feedbacks within the system. Such an understanding has hitherto been limited because the temperate marine environment has lacked an absolute timescale of the kind provided by tree-rings for the terrestrial environment and by corals for the tropical marine environment. Here we present the first annually resolved, multi-centennial (489-year), absolutely dated, shell-based marine master chronology. The chronology has been constructed by detrending and averaging annual growth increment widths in the shells of multiple specimens of the very long-lived bivalve mollusc Arctica islandica, collected from sites to the south and west of the Isle of Man in the Irish Sea. The strength of the common environmental signal expressed in the chronology is fully comparable with equivalent statistics for tree-ring chronologies. Analysis of the 14C signal in the shells shows no trend in the marine radiocarbon reservoir correction (DR), although it may be more variable before ~1750. The d13C signal shows a very significant (R**2 = 0.456, p < 0.0001) trend due to the 13C Suess effect.

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Multi-camera 3D tracking systems with overlapping cameras represent a powerful mean for scene analysis, as they potentially allow greater robustness than monocular systems and provide useful 3D information about object location and movement. However, their performance relies on accurately calibrated camera networks, which is not a realistic assumption in real surveillance environments. Here, we introduce a multi-camera system for tracking the 3D position of a varying number of objects and simultaneously refin-ing the calibration of the network of overlapping cameras. Therefore, we introduce a Bayesian framework that combines Particle Filtering for tracking with recursive Bayesian estimation methods by means of adapted transdimensional MCMC sampling. Addi-tionally, the system has been designed to work on simple motion detection masks, making it suitable for camera networks with low transmission capabilities. Tests show that our approach allows a successful performance even when starting from clearly inaccurate camera calibrations, which would ruin conventional approaches.

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In this paper we will see how the efficiency of the MBS simulations can be improved in two different ways, by considering both an explicit and implicit semi-recursive formulation. The explicit method is based on a double velocity transformation that involves the solution of a redundant but compatible system of equations. The high computational cost of this operation has been drastically reduced by taking into account the sparsity pattern of the system. Regarding this, the goal of this method is the introduction of MA48, a high performance mathematical library provided by Harwell Subroutine Library. The second method proposed in this paper has the particularity that, depending on the case, between 70 and 85% of the computation time is devoted to the evaluation of forces derivatives with respect to the relative position and velocity vectors. Keeping in mind that evaluating these derivatives can be decomposed into concurrent tasks, the main goal of this paper lies on a successful and straightforward parallel implementation that have led to a substantial improvement with a speedup of 3.2 by keeping all the cores busy in a quad-core processor and distributing the workload between them, achieving on this way a huge time reduction by doing an ideal CPU usage

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La diabetes mellitus es una enfermedad que se caracteriza por la nula o insuficiente producción de insulina, o la resistencia del organismo a la misma. La insulina es una hormona que ayuda a que la glucosa (por ejemplo la obtenida a partir de los alimentos ingeridos) llegue a los tejidos periféricos y al sistema nervioso para suministrar energía. Hoy en día la tecnología actual permite abordar el desarrollo del llamado “páncreas endocrino artificial”, que consta de un sensor continuo de glucosa subcutánea, una bomba de infusión subcutánea de insulina y un algoritmo de control en lazo cerrado que calcule la dosis de insulina requerida por el paciente en cada momento, según la medida de glucosa obtenida por el sensor y según unos objetivos. El mayor problema que presentan los sistemas de control en lazo cerrado son los retardos, el sensor de glucosa subcutánea mide la glucosa del líquido intersticial, que representa la que hubo en la sangre un tiempo atrás, por tanto, un cambio en los niveles de glucosa en la sangre, debidos por ejemplo, a una ingesta, tardaría un tiempo en ser detectado por el sensor. Además, una dosis de insulina suministrada al paciente, tarda un tiempo aproximado de 20-30 minutos para la llegar a la sangre. Para evitar trabajar en la medida que sea posible con estos retardos, se intenta predecir cuál será el nivel de glucosa en un futuro próximo, para ello se utilizara un predictor de glucosa subcutánea, con la información disponible de glucosa e insulina. El objetivo del proyecto es diseñar una metodología para estimar el valor futuro de los niveles de glucosa obtenida a partir de un sensor subcutáneo, basada en la identificación recursiva del sistema glucorregulatorio a través de modelos lineales y determinando un horizonte de predicción óptimo de trabajo y analizando la influencia de la insulina en los resultados de la predicción. Se ha implementado un predictor paramétrico basado en un modelo autorregresivo ARX que predice con mejor precisión y con menor RMSE que un predictor ZOH a un horizonte de predicción de treinta minutos. Utilizar información relativa a la insulina no tiene efecto en la predicción. El preprocesado, postprocesado y el tratamiento de la estabilidad tienen un efecto muy beneficioso en la predicción. Diabetes mellitusis a group of metabolic diseases in which a person has high blood sugar, either because the body does not produce enough insulin, or because cells do not respond to the insulin produced. The insulin is a hormone that helps the glucose to reach to outlying tissues and the nervous system to supply energy. Nowadays, the actual technology allows raising the development of the “artificial endocrine pancreas”. It involves a continuous glucose sensor, an insulin bump, and a full closed loop algorithm that calculate the insulin units required by patient at any time, according to the glucose measure obtained by the sensor and any target. The main problem of the full closed loop systems is the delays, the glucose sensor measures the glucose in the interstitial fluid that represents the glucose was in the blood some time ago. Because of this, a change in the glucose in blood would take some time to be detected by the sensor. In addition, insulin units administered by a patient take about 20-30 minutes to reach the blood stream. In order to avoid this effect, it will try to predict the glucose level in the near future. To do that, a subcutaneous glucose predictor is used to predict the future glucose with the information about insulin and glucose. The goal of the proyect is to design a method in order to estimate the future valor of glucose obtained by a subcutaneous sensor. It is based on the recursive identification of the regulatory system through the linear models, determining optimal prediction horizon and analyzing the influence of insuline on the prediction results. A parametric predictor based in ARX autoregressive model predicts with better precision and with lesser RMSE than ZOH predictor in a thirty minutes prediction horizon. Using the relative insulin information has no effect in the prediction. The preprocessing, the postprocessing and the stability treatment have many advantages in the prediction.

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This paper introduces a novel technique for identifying logically related sections of the heap such as recursive data structures, objects that are part of the same multi-component structure, and related groups of objects stored in the same collection/array. When combined withthe lifetime properties of these structures, this information can be used to drive a range of program optimizations including pool allocation, object co-location, static deallocation, and region-based garbage collection. The technique outlined in this paper also improves the efficiency of the static analysis by providing a normal form for the abstract models (speeding the convergence of the static analysis). We focus on two techniques for grouping parts of the heap. The first is a technique for precisely identifying recursive data structures in object-oriented programs based on the types declared in the program. The second technique is a novel method for grouping objects that make up the same composite structure and that allows us to partition the objects stored in a collection/array into groups based on a similarity relation. We provide a parametric component in the similarity relation in order to support specific analysis applications (such as a numeric analysis which would need to partition the objects based on numeric properties of the fields). Using the Barnes-Hut benchmark from the JOlden suite we show how these grouping methods can be used to identify various types of logical structures allowing the application of many region-based program optimizations.

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Information generated by abstract interpreters has long been used to perform program specialization. Additionally, if the abstract interpreter generates a multivariant analysis, it is also possible to perform múltiple specialization. Information about valúes of variables is propagated by simulating program execution and performing fixpoint computations for recursive calis. In contrast, traditional partial evaluators (mainly) use unfolding for both propagating valúes of variables and transforming the program. It is known that abstract interpretation is a better technique for propagating success valúes than unfolding. However, the program transformations induced by unfolding may lead to important optimizations which are not directly achievable in the existing frameworks for múltiple specialization based on abstract interpretation. The aim of this work is to devise a specialization framework which integrates the better information propagation of abstract interpretation with the powerful program transformations performed by partial evaluation, and which can be implemented via small modifications to existing generic abstract interpreters. With this aim, we will relate top-down abstract interpretation with traditional concepts in partial evaluation and sketch how the sophisticated techniques developed for controlling partial evaluation can be adapted to the proposed specialization framework. We conclude that there can be both practical and conceptual advantages in the proposed integration of partial evaluation and abstract interpretation.

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Bruynooghe described a framework for the top-down abstract interpretation of logic programs. In this framework, abstract interpretation is carried out by constructing an abstract and-or tree in a top-down fashion for a given query and program. Such an abstract interpreter requires fixpoint computation for programs which contain recursive predicates. This paper presents in detail a fixpoint algorithm that has been developed for this purpose and the motivation behind it. We start off by describing a simple-minded algorithm. After pointing out its shortcomings, we present a series of refinements to this algorithm, until we reach the final version. The aim is to give an intuitive grasp and provide justification for the relative complexity of the final algorithm. We also present an informal proof of correctness of the algorithm and some results obtained from an implementation.

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En esta tesis se presenta una nueva aproximación para la realización de mapas de calidad del aire, con objeto de que esta variable del medio físico pueda ser tenida en cuenta en los procesos de planificación física o territorial. La calidad del aire no se considera normalmente en estos procesos debido a su composición y a la complejidad de su comportamiento, así como a la dificultad de contar con información fiable y contrastada. Además, la variabilidad espacial y temporal de las medidas de calidad del aire hace que sea difícil su consideración territorial y exige la georeferenciación de la información. Ello implica la predicción de medidas para lugares del territorio donde no existen datos. Esta tesis desarrolla un modelo geoestadístico para la predicción de valores de calidad del aire en un territorio. El modelo propuesto se basa en la interpolación de las medidas de concentración de contaminantes registradas en las estaciones de monitorización, mediante kriging ordinario, previa homogeneización de estos datos para eliminar su carácter local. Con el proceso de eliminación del carácter local, desaparecen las tendencias de las series muestrales de datos debidas a las variaciones temporales y espaciales de la calidad del aire. La transformación de los valores de calidad del aire en cantidades independientes del lugar de muestreo, se realiza a través de parámetros de uso del suelo y de otras variables características de la escala local. Como resultado, se obtienen unos datos de entrada espacialmente homogéneos, que es un requisito fundamental para la utilización de cualquier algoritmo de interpolación, en concreto, del kriging ordinario. Después de la interpolación, se aplica una retransformación de los datos para devolver el carácter local al mapa final. Para el desarrollo del modelo, se ha elegido como área de estudio la Comunidad de Madrid, por la disponibilidad de datos reales. Estos datos, valores de calidad del aire y variables territoriales, se utilizan en dos momentos. Un momento inicial, donde se optimiza la selección de los parámetros más adecuados para la eliminación del carácter local de las medidas y se desarrolla cada una de las etapas del modelo. Y un segundo momento, en el que se aplica en su totalidad el modelo desarrollado y se contrasta su eficacia predictiva. El modelo se aplica para la estimación de los valores medios y máximos de NO2 del territorio de estudio. Con la implementación del modelo propuesto se acomete la territorialización de los datos de calidad del aire con la reducción de tres factores clave para su efectiva integración en la planificación territorial o en el proceso de toma de decisiones asociado: incertidumbre, tiempo empleado para generar la predicción y recursos (datos y costes) asociados. El modelo permite obtener una predicción de valores del contaminante objeto de análisis en unas horas, frente a los periodos de modelización o análisis requeridos por otras metodologías. Los recursos necesarios son mínimos, únicamente contar con los datos de las estaciones de monitorización del territorio que, normalmente, están disponibles en las páginas web viii institucionales de los organismos gestores de las redes de medida de la calidad del aire. Por lo que respecta a las incertidumbres de la predicción, puede decirse que los resultados del modelo propuesto en esta tesis son estadísticamente muy correctos y que los errores medios son, en general, similares o menores que los encontrados con la aplicación de las metodologías existentes. ABSTRACT This thesis presents a new approach for mapping air quality, so that this variable of physical environment can be taken into account in physical or territorial planning. Ambient air quality is not normally considered in territorial planning mainly due to the complexity of its composition and behavior and the difficulty of counting with reliable and contrasted information. In addition, the wide spatial and temporal variability of the measurements of air quality makes his territorial consideration difficult and requires georeferenced information. This involves predicting measurements in the places of the territory where there are no data. This thesis develops a geostatistical model for predicting air quality values in a territory. The proposed model is based on the interpolation of measurements of pollutants from the monitoring stations, using ordinary kriging, after a detrending or removal of the local character of sampling values process. With the detrending process, the local character of the time series of sampling data, due to temporal and spatial variations of air quality, is removed. The transformation of the air quality values into site-independent quantities is performed using land use parameters and other characteristic parameters of local scale. This detrending of the monitoring data process results in a spatial homogeneous input set which is a prerequisite for a correct use of any interpolation algorithm, particularly, ordinary kriging. After the interpolation step, a retrending or retransformation is applied in order to incorporate the local character in the final map at places where no monitoring data is available. For the development of this model, the Community of Madrid is chosen as study area, because of the availability of actual data. These data, air quality values and local parameters, are used in two moments. A starting point, to optimize the selection of the most suitable indicators for the detrending process and to develop each one of the model stages. And a second moment, to fully implement the developed model and to evaluate its predictive power. The model is applied to estimate the average and maximum values of NO2 in the study territory. With the implementation of the proposed model, the territorialization of air quality data is undertaken with the reduction in three key factors for the effective integration of this parameter in territorial planning or in the associated decision making process: uncertainty, time taken to generate the prediction and associated resources (data and costs). This model allows the prediction of pollutant values in hours, compared to the implementation time periods required for other modeling or analysis methodologies. The required resources are also minimal, only having data from monitoring stations in the territory, that are normally available on institutional websites of the authorities responsible for air quality networks control and management. With regard to the prediction uncertainties, it can be concluded that the results of the proposed model are statistically very accurate and the mean errors are generally similar to or lower than those found with the application of existing methodologies.

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El objetivo de esta Tesis ha sido la consecución de simulaciones en tiempo real de vehículos industriales modelizados como sistemas multicuerpo complejos formados por sólidos rígidos. Para el desarrollo de un programa de simulación deben considerarse cuatro aspectos fundamentales: la modelización del sistema multicuerpo (tipos de coordenadas, pares ideales o impuestos mediante fuerzas), la formulación a utilizar para plantear las ecuaciones diferenciales del movimiento (coordenadas dependientes o independientes, métodos globales o topológicos, forma de imponer las ecuaciones de restricción), el método de integración numérica para resolver estas ecuaciones en el tiempo (integradores explícitos o implícitos) y finalmente los detalles de la implementación realizada (lenguaje de programación, librerías matemáticas, técnicas de paralelización). Estas cuatro etapas están interrelacionadas entre sí y todas han formado parte de este trabajo. Desde la generación de modelos de una furgoneta y de camión con semirremolque, el uso de tres formulaciones dinámicas diferentes, la integración de las ecuaciones diferenciales del movimiento mediante métodos explícitos e implícitos, hasta el uso de funciones BLAS, de técnicas de matrices sparse y la introducción de paralelización para utilizar los distintos núcleos del procesador. El trabajo presentado en esta Tesis ha sido organizado en 8 capítulos, dedicándose el primero de ellos a la Introducción. En el Capítulo 2 se presentan dos formulaciones semirrecursivas diferentes, de las cuales la primera está basada en una doble transformación de velocidades, obteniéndose las ecuaciones diferenciales del movimiento en función de las aceleraciones relativas independientes. La integración numérica de estas ecuaciones se ha realizado con el método de Runge-Kutta explícito de cuarto orden. La segunda formulación está basada en coordenadas relativas dependientes, imponiendo las restricciones por medio de penalizadores en posición y corrigiendo las velocidades y aceleraciones mediante métodos de proyección. En este segundo caso la integración de las ecuaciones del movimiento se ha llevado a cabo mediante el integrador implícito HHT (Hilber, Hughes and Taylor), perteneciente a la familia de integradores estructurales de Newmark. En el Capítulo 3 se introduce la tercera formulación utilizada en esta Tesis. En este caso las uniones entre los sólidos del sistema se ha realizado mediante uniones flexibles, lo que obliga a imponer los pares por medio de fuerzas. Este tipo de uniones impide trabajar con coordenadas relativas, por lo que la posición del sistema y el planteamiento de las ecuaciones del movimiento se ha realizado utilizando coordenadas Cartesianas y parámetros de Euler. En esta formulación global se introducen las restricciones mediante fuerzas (con un planteamiento similar al de los penalizadores) y la estabilización del proceso de integración numérica se realiza también mediante proyecciones de velocidades y aceleraciones. En el Capítulo 4 se presenta una revisión de las principales herramientas y estrategias utilizadas para aumentar la eficiencia de las implementaciones de los distintos algoritmos. En primer lugar se incluye una serie de consideraciones básicas para aumentar la eficiencia numérica de las implementaciones. A continuación se mencionan las principales características de los analizadores de códigos utilizados y también las librerías matemáticas utilizadas para resolver los problemas de álgebra lineal tanto con matrices densas como sparse. Por último se desarrolla con un cierto detalle el tema de la paralelización en los actuales procesadores de varios núcleos, describiendo para ello el patrón empleado y las características más importantes de las dos herramientas propuestas, OpenMP y las TBB de Intel. Hay que señalar que las características de los sistemas multicuerpo problemas de pequeño tamaño, frecuente uso de la recursividad, y repetición intensiva en el tiempo de los cálculos con fuerte dependencia de los resultados anteriores dificultan extraordinariamente el uso de técnicas de paralelización frente a otras áreas de la mecánica computacional, tales como por ejemplo el cálculo por elementos finitos. Basándose en los conceptos mencionados en el Capítulo 4, el Capítulo 5 está dividido en tres secciones, una para cada formulación propuesta en esta Tesis. En cada una de estas secciones se describen los detalles de cómo se han realizado las distintas implementaciones propuestas para cada algoritmo y qué herramientas se han utilizado para ello. En la primera sección se muestra el uso de librerías numéricas para matrices densas y sparse en la formulación topológica semirrecursiva basada en la doble transformación de velocidades. En la segunda se describe la utilización de paralelización mediante OpenMP y TBB en la formulación semirrecursiva con penalizadores y proyecciones. Por último, se describe el uso de técnicas de matrices sparse y paralelización en la formulación global con uniones flexibles y parámetros de Euler. El Capítulo 6 describe los resultados alcanzados mediante las formulaciones e implementaciones descritas previamente. Este capítulo comienza con una descripción de la modelización y topología de los dos vehículos estudiados. El primer modelo es un vehículo de dos ejes del tipo chasis-cabina o furgoneta, perteneciente a la gama de vehículos de carga medianos. El segundo es un vehículo de cinco ejes que responde al modelo de un camión o cabina con semirremolque, perteneciente a la categoría de vehículos industriales pesados. En este capítulo además se realiza un estudio comparativo entre las simulaciones de estos vehículos con cada una de las formulaciones utilizadas y se presentan de modo cuantitativo los efectos de las mejoras alcanzadas con las distintas estrategias propuestas en esta Tesis. Con objeto de extraer conclusiones más fácilmente y para evaluar de un modo más objetivo las mejoras introducidas en la Tesis, todos los resultados de este capítulo se han obtenido con el mismo computador, que era el top de la gama Intel Xeon en 2007, pero que hoy día está ya algo obsoleto. Por último los Capítulos 7 y 8 están dedicados a las conclusiones finales y las futuras líneas de investigación que pueden derivar del trabajo realizado en esta Tesis. Los objetivos de realizar simulaciones en tiempo real de vehículos industriales de gran complejidad han sido alcanzados con varias de las formulaciones e implementaciones desarrolladas. ABSTRACT The objective of this Dissertation has been the achievement of real time simulations of industrial vehicles modeled as complex multibody systems made up by rigid bodies. For the development of a simulation program, four main aspects must be considered: the modeling of the multibody system (types of coordinates, ideal joints or imposed by means of forces), the formulation to be used to set the differential equations of motion (dependent or independent coordinates, global or topological methods, ways to impose constraints equations), the method of numerical integration to solve these equations in time (explicit or implicit integrators) and the details of the implementation carried out (programming language, mathematical libraries, parallelization techniques). These four stages are interrelated and all of them are part of this work. They involve the generation of models for a van and a semitrailer truck, the use of three different dynamic formulations, the integration of differential equations of motion through explicit and implicit methods, the use of BLAS functions and sparse matrix techniques, and the introduction of parallelization to use the different processor cores. The work presented in this Dissertation has been structured in eight chapters, the first of them being the Introduction. In Chapter 2, two different semi-recursive formulations are shown, of which the first one is based on a double velocity transformation, thus getting the differential equations of motion as a function of the independent relative accelerations. The numerical integration of these equations has been made with the Runge-Kutta explicit method of fourth order. The second formulation is based on dependent relative coordinates, imposing the constraints by means of position penalty coefficients and correcting the velocities and accelerations by projection methods. In this second case, the integration of the motion equations has been carried out by means of the HHT implicit integrator (Hilber, Hughes and Taylor), which belongs to the Newmark structural integrators family. In Chapter 3, the third formulation used in this Dissertation is presented. In this case, the joints between the bodies of the system have been considered as flexible joints, with forces used to impose the joint conditions. This kind of union hinders to work with relative coordinates, so the position of the system bodies and the setting of the equations of motion have been carried out using Cartesian coordinates and Euler parameters. In this global formulation, constraints are introduced through forces (with a similar approach to the penalty coefficients) are presented. The stabilization of the numerical integration is carried out also by velocity and accelerations projections. In Chapter 4, a revision of the main computer tools and strategies used to increase the efficiency of the implementations of the algorithms is presented. First of all, some basic considerations to increase the numerical efficiency of the implementations are included. Then the main characteristics of the code’ analyzers used and also the mathematical libraries used to solve linear algebra problems (both with dense and sparse matrices) are mentioned. Finally, the topic of parallelization in current multicore processors is developed thoroughly. For that, the pattern used and the most important characteristics of the tools proposed, OpenMP and Intel TBB, are described. It needs to be highlighted that the characteristics of multibody systems small size problems, frequent recursion use and intensive repetition along the time of the calculation with high dependencies of the previous results complicate extraordinarily the use of parallelization techniques against other computational mechanics areas, as the finite elements computation. Based on the concepts mentioned in Chapter 4, Chapter 5 is divided into three sections, one for each formulation proposed in this Dissertation. In each one of these sections, the details of how these different proposed implementations have been made for each algorithm and which tools have been used are described. In the first section, it is shown the use of numerical libraries for dense and sparse matrices in the semirecursive topological formulation based in the double velocity transformation. In the second one, the use of parallelization by means OpenMP and TBB is depicted in the semi-recursive formulation with penalization and projections. Lastly, the use of sparse matrices and parallelization techniques is described in the global formulation with flexible joints and Euler parameters. Chapter 6 depicts the achieved results through the formulations and implementations previously described. This chapter starts with a description of the modeling and topology of the two vehicles studied. The first model is a two-axle chassis-cabin or van like vehicle, which belongs to the range of medium charge vehicles. The second one is a five-axle vehicle belonging to the truck or cabin semi-trailer model, belonging to the heavy industrial vehicles category. In this chapter, a comparative study is done between the simulations of these vehicles with each one of the formulations used and the improvements achieved are presented in a quantitative way with the different strategies proposed in this Dissertation. With the aim of deducing the conclusions more easily and to evaluate in a more objective way the improvements introduced in the Dissertation, all the results of this chapter have been obtained with the same computer, which was the top one among the Intel Xeon range in 2007, but which is rather obsolete today. Finally, Chapters 7 and 8 are dedicated to the final conclusions and the future research projects that can be derived from the work presented in this Dissertation. The objectives of doing real time simulations in high complex industrial vehicles have been achieved with the formulations and implementations developed.

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Markov Chain Monte Carlo methods are widely used in signal processing and communications for statistical inference and stochastic optimization. In this work, we introduce an efficient adaptive Metropolis-Hastings algorithm to draw samples from generic multimodal and multidimensional target distributions. The proposal density is a mixture of Gaussian densities with all parameters (weights, mean vectors and covariance matrices) updated using all the previously generated samples applying simple recursive rules. Numerical results for the one and two-dimensional cases are provided.